import gradio as gr
import plotly.graph_objects as go

import torch
from tqdm.auto import tqdm

from model import Model
from settings import CACHE_EXAMPLES, MAX_SEED
from utils import randomize_seed_fn


def inference(prompt):
    model = Model()
    seed: int = 0
    guidance_scale: float = 15.0
    num_inference_steps: int = 64
    
    return model.run_text(prompt, seed, guidance_scale, num_inference_steps)
    
demo = gr.Interface(
    fn=inference,
    inputs="text",
    outputs=gr.Textbox(label = "Text Genereated", lines = 5),
    examples=[
        ["a red motorcycle"],
        ["a RED pumpkin"],
        ["a yellow rubber duck"]
    ],
    title="Point-E demo: text to 3D",
    description="""Generated 3D Point Clouds with [Point-E](https://github.com/openai/point-e/tree/main). This demo uses a small, worse quality text-to-3D model to produce 3D point clouds directly from text descriptions.
    Check out the [notebook](https://github.com/openai/point-e/blob/main/point_e/examples/text2pointcloud.ipynb).
"""
)
demo.queue(max_size=30)
demo.launch(debug=True)